How do friendship and advice ties emerge' A case study of graduate student social networks

Aditya Tyagi, Diego Gomez-Zara, Noshir S. Contractor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we analyze the factors that are most likely to explain the formation of friendship and advice ties among 44 students from a professional STEM graduate program. To answer our research questions, we investigate how students' characteristics influence the formation of their friendship and advice networks using descriptive network analysis, community detection, and Exponential Random Graph Models. The results show that the formation of friendship and advice ties is mostly driven by demographic homophily and prior group activities. Our findings also suggest that female students were more constrained in their friendship and advice networks than male students. We discuss the implications of these results for how graduate students' social networks form at the beginning of their program.

Original languageEnglish (US)
Title of host publicationProceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020
EditorsMartin Atzmuller, Michele Coscia, Rokia Missaoui
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages578-585
Number of pages8
ISBN (Electronic)9781728110561
DOIs
StatePublished - Dec 7 2020
Event12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020 - Virtual, Online, Netherlands
Duration: Dec 7 2020Dec 10 2020

Publication series

NameProceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020

Conference

Conference12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020
Country/TerritoryNetherlands
CityVirtual, Online
Period12/7/2012/10/20

Keywords

  • community detection
  • exponential random graph models
  • Homophily
  • minorities
  • network analysis
  • personality

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Social Psychology
  • Communication

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